生态系统水分利用效率(water use efficiency,WUE)连接了碳循环和水循环,是碳水耦合的重要参数。全面深入理解WUE的时空分布及其影响因素对预测陆地表面-大气相互作用和陆地生态系统的动态变化至关重要。该文基于大尺度遥感归一化植被指数(normalization difference vegetation index,NDVI)以及温度和降水栅格数据,采用中分辨率成像光谱仪的总初级生产力和蒸散产品计算20002014年黄土高原生态系统WUE,运用岭回归探究黄土高原WUE对温度、降水和NDVI的敏感性。结果表明:1)沿西北-东南随降水量的增加,黄土高原多年均WUE逐渐降低,且黄土高原西南部高海拔地区WUE最低;同时,WUE的年际变化明显,以2011年为转折点,20122014年WUE明显高于其他年份。2)WUE对温度的敏感性在整个黄土高原呈现正值,WUE对降水和NDVI的敏感性存在阈值效应,即小于500 mm降水量,WUE随降水和NDVI的增加而升高,超过550 mm降水量,WUE则随降水和NDVI增加而降低。3)草地和灌丛WUE与NDVI正相关,森林WUE与NDVI负相关;灌丛WUE对温度和降水的敏感度明显高于森林和草地。
英文摘要:
Water use efficiency (WUE) refers to the amount of CO_2 or dry matter produced by per unit consumed water by plants, which is an important indicator of carbon-water coupling. A comprehensive understanding of spatial and temporal distribution and influencing factors of WUE is crucial for predicting land surface-atmosphere interactions and future dynamics of terrestrial ecosystems in response to future climate warming. In this study, we analyzed the response of WUE to precipitation, air temperature and vegetation index in Loess Plateau. Data were obtained from well-established products from moderate resolution imaging spectroradiometer (MODIS). The data of gross primary productivity (GPP) and evapotranspiration (ET) were from the MOD17A3 and MOD16A3, respectively. The data had been validated. WUE was the ratio of GPP to ET. Gridded precipitation and air temperature data were interpolated by ANUSPLIN software, and the satellite-derived normalized difference vegetation index (NDVI) was from Advanced Very High Resolution Radiometer (AVHRR)/ National Oceanographic and Atmospheric Agency (NOAA), all the data in this article were resampled to 1 km resolution. The duration was from the year of 2000 to 2014. Land coverage was classified by CMG products (MCD12Q1) with resolution of 1 km. The analysis focused mainly on 3 natural vegetation groups because cultivated vegetation had experienced intensive human management in Loess plateau. The growing season was consequently defined as the duration from March to October. All the variables were detrended by linear fitting before performing the ridge regression using MATLAB. When applying ridge regression to explore the sensitivity of WUE to temperature, precipitation and NDVI, WUE was dependent variable, and temperature, precipitation and NDVI were dependent variables. The results showed that: 1) GPP, ET and WUE distribution had an obvious spatial and temporal pattern in Loess Plateau. The GPP and ET gradually reduced with increasing precipitation. Forest had the highest GPP and ET and shrubland had the lowest GPP and ET. The lowest WUE was found in the southwest of Loess plateau, which was an higher altitude area. Mean annual WUE decreased with increasing precipitation. The interannual variation of GPP, ET and WUE were also obvious, the same variation trend were found in WUE and GPP, which were significantly higher in the year of 2012, 2013 and 2014 than the other years. But the ET didn't showed obvious variation regulation. 2) The sensitivity of WUE to air temperature, precipitation and NDVI showed significant spatial divergence. the sensitivity of WUE to temperature was significantly positive in the whole Loess plateau. The sensitivity of WUE to precipitation and NDVI presented a threshold effect, i.e., WUE increased with precipitation and NDVI when precipitation was less than 500 mm, WUE decreased with precipitation and NDVI when precipitation was over 550 mm. 3) The sensitivity of WUE to air temperature, precipitation and NDVI were related to vegetation type. The NDVI was positively correlated with the WUE of grassland and shrubland, and negatively correlated with the WUE of forest. The sensitivity of WUE of shrubland to temperature and precipitation was significantly higher than that of forest and grassland. This research is helpful in understanding the climate adaptation mechanism of ecosystem under the background of future climate and land use cover change in Loess Plateau.